Item Response Theory Analysis of DSM-IV Cannabis Abuse and Dependence Criteria in Adolescents

An Item Response Theory Analysis of DSM-IV Cannabis Abuseand Dependence Criteria in Adolescents

Christie A. Hartman, Ph.D., Heather Gelhorn, Ph.D., Thomas J. Crowley, M.D., Joseph T.Sakai, M.D., Michael Stallings, Ph.D., Susan E. Young, Ph.D., Soo Hyun Rhee, Ph.D., RobinCorley, Ph.D., John K. Hewitt, Ph.D., and Christian J. Hopfer, M.D.Christie Hartman, Heather Gelhorn, Thomas Crowley, Joseph Sakai, and Christian Hopfer are allaffiliated with the School of Medicine at the University of Colorado Health Sciences Center in Denver,CO. Michael Stallings, Susan Young, Soo Hyun Rhee, RobinCorley, and John Hewitt are affiliatedwith the Institute for Behavioral Genetics at the University of Colorado at Boulder

AbstractObjective—To examine three aspects of adolescent cannabis problems: 1) do DSM-IV cannabisabuse and dependence criteria represent two different levels of severity of substance involvement,2) to what degree do each of the 11 abuse and dependence criteria assess adolescent cannabisproblems, and 3) do the DSM-IV items function similarly across different adolescent populations?

Method—We examined 5587 adolescents aged 11–19, including 615 youth in treatment forsubstance use disorders, 179 adjudicated youth, and 4793 youth from the community. All subjectswere assessed with a structured diagnostic interview. Item response theory was utilized to analyzesymptom endorsement patterns.

Results—Abuse and dependence criteria were not found to represent different levels of severity ofproblem cannabis use in any of the samples. Among the 11 abuse and dependence criteria, Problemscutting down and Legal problems were the least informative for distinguishing problem users. Twodependence criteria and three of the four abuse criteria indicated different severities of cannabisproblems across samples.

Conclusions—We found little evidence to support the idea that abuse and dependence are separateconstructs for adolescent cannabis problems. Furthermore, certain abuse criteria may indicate severesubstance problems while specific dependence items may indicate less severe problems. The abuseitems in particular need further study. These results have implications for the refinement of the currentsubstance use disorder criteria for DSM-V.

KeywordsItem Response Theory; cannabis abuse; cannabis dependence; DSM-IV; DSM-V

INTRODUCTIONIn anticipation of the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-V), researchers are examining the utility of the DSM-IV criteria for substance use disorders1, 2. Many of these studies have examined the abuse and dependence constructs, and theindividual criteria that comprise them. Much of the work that led to the distinction betweenabuse and dependence derives from studies of adults with alcohol use disorders 3, 4. Fewstudies have examined DSM-IV criteria for cannabis use disorders, and in particular, whether

Corresponding Author: Christie Hartman, 4200 East 9th Ave, Box C268-35, Denver, CO 80262, Phone:303315-0606, Fax 303-315-0394,Email: [email protected].

NIH Public AccessAuthor ManuscriptJ Am Acad Child Adolesc Psychiatry. Author manuscript; available in PMC 2008 July 7.

Published in final edited form as:J Am Acad Child Adolesc Psychiatry. 2008 February ; 47(2): 165–173.

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diagnostic distinctions such as abuse or dependence are meaningful for these disorders.Furthermore, studies of adolescents are even less common.

One reason to examine DSM-IV criteria for cannabis abuse and dependence in adolescents isthat it is the most commonly used illicit substance among U.S. adolescents 5. According to theMonitoring the Future study, in 2005 49% of 12th graders reported having tried cannabis atsome point in their lifetime, 30% used within the past month, and 5% smoked cannabis daily5. Cannabis dependence develops in approximately 10–14% of adolescent-onset users versusin about 8% of adult-onset users 6–8. Adolescents and young adults represent the majority ofpatients admitted to publicly funded treatment facilities for cannabis use disorders. Youthsaged 12 to 17 constitute about two thirds of such admissions, with young adults aged 18 to 25constituting most of the remaining third 9. Thus, cannabis use is frequent among adolescents,develops into dependence among a substantial proportion of users, and represents a significantpublic health burden.

Very few studies have examined the DSM-IV criteria for cannabis use disorders, in contrastto the extensive literature on alcohol disorders. An important point of discussion in the adultalcohol use disorder literature is the separation of alcohol abuse and dependence into separateconstructs, where abuse is a less severe construct reflecting the social or legal consequencesof drinking versus the more severe dependence construct reflecting the physiological,cognitive, and psychosocial aspects of dependence 3. Subsequent factor analytic 10–13 andlongitudinal 4, 14–16 studies examining alcohol as well as illicit drugs support thisconceptualization. However, others examining the distinction at the item level have questionedit, showing weak support for the abuse construct 10, 11, 17, 18, for the separation of abuse anddependence 19–22, and for dependence being more severe than abuse 21, 22.

To examine whether cannabis abuse and dependence criteria represent different measures ofproblem cannabis use, Teesson et al 23 utilized factor analytic methods to examine the structureof cannabis abuse and dependence in an Australian adult population sample. Cannabis abuseand dependence reflected a common liability, with abuse and dependence factors correlatingat 0.99. On the other hand, Winters et al. 16 found evidence for the abuse-dependencedistinction with adolescent cannabis use. Other studies found good support for the validity ofcannabis dependence, but less support for abuse 10, 11, 24, 25, consistent with studiesexamining alcohol and other drugs 17, 18. However, more studies examining the properties ofindividual abuse and dependence items need to be conducted before any firm conclusions canbe drawn.

Item Response Theory (IRT) is a method that allows researchers to examine not only the abuseand dependence constructs, but the properties of the criteria that comprise them. Typically,researchers who study abuse and dependence either examine these categories as defined byDSM-IV, or utilize symptom counts as a continuous measure of substance involvement. Whendeveloping constructs such as abuse or dependence, factor analysis is a commonly used methodto test whether individual criteria cluster together in a single “factor” 12. IRT has a fewadvantages over factor analysis; when examining a series of items such as the DSM-IVsubstance use disorder criteria, rather than simply adding the number of criteria endorsed byan individual, IRT examines which particular criteria are endorsed by each individual, allowingthat criteria may not have equal “weight” in predicting substance use problems. Thus, IRTestimates how informative a particular item is as well as how useful it is in predicting theseverity of pathology in those who endorse it. Heuristically, it is helpful to think of IRT throughthe example of a test of mathematical ability – easier questions will be answered correctly bymore of the test takers and harder questions by fewer. Thus, instead of simply “counting” howmany questions one answered correctly, IRT examines which questions were answeredcorrectly and judges the “mathematical ability” of the test taker by this pattern. Similarly, each

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question would be rated as “harder” or “easier” based upon the patterns of endorsement. In thecontext of substance problems, certain criteria may be endorsed only by more severely affectedindividuals who endorse many symptoms, whereas other criteria may be endorsed by many,including those who endorse only one or two symptoms.

A few studies have used IRT to examine the DSM-IV cannabis abuse and dependence criteria.Langenbucher et al. 22 examined alcohol, cannabis, and cocaine criteria in 372 adults intreatment for substance abuse and found no evidence supporting the separation of abuse anddependence into separate diagnoses. Teesson et al. 23 performed an IRT analysis of the DSM-IV cannabis items in a general population sample of adults and found that three of the fourcannabis abuse items showed high severity levels, suggesting that abuse may indicate greaterseverity of substance use problems than previously thought.

Very few studies have examined the DSM-IV criteria for cannabis use in adolescents, and itis important to do so because adolescents may show different abuse or dependence patternsthan adults. For example, alcohol abuse symptoms are more common in adolescents and youngadults than in adults 26. Winters et al. 16 reported that DSM-IV criteria resulted in more alcoholand cannabis abuse diagnoses and fewer dependence diagnoses compared to theDSM-III-R inan adolescent clinical sample. Martin et al. 27 utilized IRT methods to examine the DSM-IVcriteria for both alcohol and cannabis in an adolescent clinical sample. They found no evidencesupporting the separation of abuse and dependence items for adolescent alcohol or cannabisdisorders, and also found no evidence supporting the greater severity of dependence over abuse.Their results have not been replicated in other adolescent samples, and it is particularlyimportant to conduct these analyses in community samples, as highly selected samples maybe less useful for estimating the characteristics of individual items in a way that will beinformative in the development of diagnostic definitions.

Adolescents may also show different criteria endorsement patterns than adults. For example,in a review of studies examining alcohol use disorders in adolescents, Martin & Winters 26reported that adolescents don’t often experience dependence symptoms such as Withdrawal orUse despite health problems, or abuse symptoms such as Use in hazardous situations (e.g.driving drunk) or Legal problems, to the extent that adults do. Also, adolescents tend to highlyendorse the Tolerance criterion; however, Tolerance has shown limited utility in differentiatingadolescents with mild substance use problems from those with more severe ones, for bothalcohol 27 and cannabis 28. Utilizing factor analysis, Teesson et al. 23 found that Use inhazardous situations and Legal problems displayed weak loadings when examining the DSM-IV items for cannabis in an adult population sample, and Langenbucher et al. 22 found thatTolerance and Legal problems displayed weak loadings in their adult clinical sample,suggesting that these symptoms may not be very informative for adolescent substance useproblems. However, these latter two results need replication in adolescent samples.

Finally, it is important to examine whether the DSM-IV substance use criteria are adequate foruse with different populations. Adolescents in treatment may report different criteria thanadolescents in the community, and a good diagnostic system should be useful for those withmilder substance abuse problems as well as the more severe ones. Most of the literatureexamining DSM-IV substance abuse and dependence criteria has focused on alcohol, and thefew studies focusing on cannabis criteria have primarily examined adult populations.

We utilized Item Response Theory to address the following questions: One, do the cannabisabuse and dependence criteria in the DSM-IV reflect two non-overlapping levels of severityin adolescents, in which dependence is more severe than abuse? Two, to what degree do eachof the 11 items assess adolescent cannabis problems? And three, do the DSM-IV items functionsimilarly across different adolescent populations? We examined these questions in three

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samples of adolescents: a clinical (treatment) sample, an adjudicated sample, and a communitysample. Our sample is larger and provides greater diversity of substance use severity than seenin the above-cited studies.

METHODSample

We examined 5587 adolescents aged 11–19 from three different samples (Table 1): a clinicalsample of youth recruited from a substance abuse treatment center, a sample of adjudicatedyouth, and a community sample. The data examined in this project come from studies that haveIRB approval and federal certificates of confidentiality. All data were de-identified. Consent/assent forms were obtained from each subject.

Clinical sample—Adolescents from this sample come from the Colorado Family Study, acomponent of the Center for Antisocial Drug Dependence (CADD; DA 11015). Over 600adolescent probands were recruited from 1993 to 2003 from an adolescent substance abusetreatment center affiliated with the University of Colorado. Initial ascertainment andinterviewing was carried out when probands were entering residential or intensive daytreatment for adolescent substance dependence. Details regarding this sample have beenreported elsewhere 29.

Adjudicated sample—Every year, millions of adolescents are arrested, a proportion ofwhom are adjudicated (convicted and placed on probation). Those youth who were adjudicatedin the Denver metropolitan area were contacted by phone and mail and invited to participatein a study of the family transmission and comorbidity of adolescent substance use and conductdisorder (DA 015522). Those who participated (n = 202) were interviewed between 2001 and2006 using the same core instruments utilized in the clinical and community samples to allowfor comparability across samples.

Community sample—This sample includes adolescents from the Colorado Twin Registry,Colorado Adoption Project, and Family Control Samples, which are all components of theCADD. The twin sample consists of 1400 general population adolescent twin pairs, and 400siblings of twins. The adoption sample consists of 673 adoptees, matched controls and theirbiological siblings, followed since birth. A control sample collected to match the youth fromsubstance abuse treatment programs includes approximately 400 families. This sample hasbeen described elsewhere 29.

Sample used for analysis—For clinical and adjudicated samples, only probands wereanalyzed (i.e. youth identified through treatment for substance use disorders or identified asbeing adjudicated). For the community sample, the analysis was conducted by weightingsubjects within the same family to account for their relatedness. For example, data from twosiblings within a family were each weighted .5 and .5, data from three siblings were weighted .33, .33, .34, etc. This weighting procedure resulted in 2060 total observations for thecommunity sample. Basic demographic information for the combined and individual samplesis presented in Table 1.

MeasuresSubjects in all three samples were assessed for substance use with the Composite InternationalDiagnostic Interview – Substance Abuse Module (CIDI-SAM) 30, a structured, face-to-faceinterview designed to be administered by trained lay interviewers, which provides DSM-IVsymptom and diagnostic information for ten drug classes. The CIDI’s reliability and validity31 made a version of it the main assessment for DSM-IV Substance Field Trials and for the

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National Comorbidity Study 32. Its validity for use with substance dependent adolescents hasbeen demonstrated 33, 34. We currently use a version that allows us to compute symptomcounts as well as generate DSM-IV abuse and dependence diagnoses.

AnalysesFactor Analyses—We conducted an exploratory factor analysis (EFA) of the 11 cannabisabuse and dependence items using Mplus software 35. The factor analysis was conducted usingtetrachoric correlations, which are more appropriate for binary data than Pearson correlations36. Large ratios of first to second eigenvalues and a better fit of single versus multiple factormodels were utilized as evidence for unidimensionality22, 37.

IRT analyses—For simplicity, each of the 11 DSM-IV substance abuse and dependencesymptoms will be referred to as “items” throughout this paper. PARSCALE 38 was utilized toperform IRT analyses of the 11 items. A two-parameter IRT model was utilized, in which bothitem discrimination (a) and item severity (β) parameters were estimated. The itemdiscrimination (a) parameter represents the ability of that item to discriminate among thosewith latent trait levels (i.e. cannabis problems) above and below the item’s severity threshold.A higher estimate indicates better discrimination and that the item is a “good” one. The severity(β) parameter (or threshold) represents the latent trait z-score where the probability of endorsingthat item is 0.5. Thus, an item with a severity estimate of 1.5 suggests that the item is endorsed50% of the time by subjects who are at a severity level of 1.5 standard deviations above themean on the latent cannabis problems trait. Item severity is a function of the percentage ofendorsement as well as the pattern of endorsement. In other words, IRT examines not onlyhow many subjects endorse a particular item, but which subjects endorse it. A high severityestimate for a particular item suggests that the item is endorsed less frequently and is endorsedprimarily by those endorsing many other items as well, thus indicating greater severity of thelatent trait in an individual. A useful measurement scale includes items with a range of severitiesacross the latent trait, as well as high discrimination values.

In order to examine whether the DSM-IV cannabis items functioned similarly in clinical,adjudicated, and community samples, we performed a Differential Item Functioning (DIF)analysis for the items. This analysis examines whether symptom severity (β) parameters foreach item differ significantly among the samples. Significant DIF suggests that an itemindicates different levels of pathology in different samples 39. DIF for the discrimination (a)parameters were not performed due to power limitations; while β is estimated from both itemprevalence and item endorsement patterns, a is estimated from item endorsement only, andthus lacks the power necessary for DIF analyses.

RESULTSDSM-IV cannabis symptoms and diagnoses

Table 2 displays the mean symptom counts as well as the percentage of DSM-IV cannabisabuse and dependence diagnoses in the individual and combined samples. Cannabis symptomsand diagnoses were highest in the clinical sample and lowest in the community sample, withthe adjudicated sample falling between the two.

Item endorsementThe percentage of subjects in each sample who endorsed each DSM-IV cannabis abuse anddependence item is presented in Figure 1. For each item, endorsement was highest for theclinical sample and lowest for the community sample. The most highly endorsed items for allthree samples included dependence items D1 (Tolerance) and D7 (Use despite healthproblems), and abuse item A4 (Social/interpersonal problems).

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Exploratory Factor AnalysesEFA results showed a high eigenvalue ratio of first factor (eigenvalue = 7.09) to second factor(eigenvalue = 0.90) for the 11 DSM-IV items, and model fit was no worse for the moreparsimonious single factor model compared with the fit of the two factor model, suggestingthat the items collectively represent a single latent dimension.

IRT analysIndividual item parameter estimates are shown with the item characteristic curves (ICCs) inFigure 2. ICCs are a graphical display of both the discrimination (a) and severity (β) parametersfor each symptom, and allow for comparison across symptoms. Item discrimination (a)estimates, which represent the item’s ability to discriminate among those with cannabisproblems above and below the item’s severity threshold, varied from 1.31 to 2.48. Items D6(Activities given up) and D2 (Withdrawal) showed the highest discrimination ability and itemsD4 (Problems cutting down) and A3 (Legal problems) showed the lowest discrimination.

Item severity (β) parameters, which represent the cannabis problems z-score where there’s a50% probability of endorsing that item, were scaled to represent z-scores in the communitysample – in other words, the severity estimates represent severity z-scores for the generalpopulation. These estimates ranged from 1.87 to 2.87 standard deviations above the mean(Figure 2). In addition, when comparing the severity parameters across samples, the abuseestimates and dependence estimates were intermixed for all three samples, with both abuse anddependence items on the lower and upper ends of the severity spectrum (Figure 3). For example,those items indicating the greatest severity levels included abuse items A2 (Use in hazardoussituations) and A3 (Legal problems), as well as dependence item D4 (Problems cuttingdown). Conversely, dependence items D1 (Tolerance) and D7 (Use despite health problems)indicated low severity levels across all three samples, as did abuse item A4 (Social/Interpersonal problems). These results suggest that the abuse items are not necessarilyindicative of less severe pathology, and that some items may be more useful than others inidentifying adolescents with more serious cannabis problems.

The Differential Item Functioning (DIF) analyses examined whether the severity parametersfor each item differed significantly among the three samples. Omnibus results for these analysesshowed that only two dependence items functioned differently across the three samples (Figure4): D1 (Tolerance) and D3 (Larger amounts/longer period). However, there were significantdifferences among samples for three of the four abuse items (Use in hazardous situations,Legal problems, and Social/interpersonal problems). These results suggest that these five itemsindicate different levels of severity of cannabis problems in different samples.

DISCUSSIONWe utilized Item Response Theory (IRT) to examine the utility of DSM-IV cannabis abuseand dependence items in three adolescent samples: a substance abuse treatment sample, anadjudicated sample, and a community sample. This study is unique in that it is a large sampleof both community and clinically ascertained adolescents, which provides information aboutthe DSM-IV items at the population level as well as at more severe levels of cannabis use.

Abuse-dependence distinctionWhen we examined the DSM-IV cannabis item severity (β) parameters, we found that theabuse and dependence symptoms overlapped one another and varied from low to high severity.In other words, some abuse items indicated high severity of cannabis problems and somedependence itemindicated low severity of cannabis problems. For example, the dependenceitems D7 (Use despite health problems) and D1 (Tolerance) indicated lower severity levels in

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all three samples. These items were two of the more highly endorsed items (Figure 1), and thuswere likely endorsed by those with low levels of cannabis problems as well as high levels. Onthe other hand, abuse items A2 (Use in hazardous situations) and A3 (Legal problems) tendedto indicate a higher level of severity. This is similar to the results of Teesson et al. 23, whoreported that three of the four cannabis abuse items showed higher severity estimates than mostof the dependence criteria. Thus, the cannabis abuse criteria may, in fact, indicate seriouscannabis problems.

Overall, these results cast doubt upon the assumption in the literature that cannabis dependenceis more severe than abuse, and add to a growing number of studies that have examined alcohol,cannabis, and other drugs in adolescents and adults and come to similar conclusions. And whilethe DSM-IV doesn’t explicitly state that a substance dependence diagnosis is more severe thanan abuse diagnosis, it is implied by the fact that an abuse diagnosis cannot be assigned oncecriteria are met for dependence, and it is commonly stated outright in the literature. And whilesome have suggested that individuals with a dependence diagnosis fare worse than those withan abuse diagnosis 16, others have made it clear that the individual abuse items indicate highlevels of severity of substance problems 23, suggesting that some other factor, perhaps thenumber of symptoms required for diagnosis, may need more examination. Thus, the DSM-Vmight consider removing the requirement that an abuse diagnosis cannot be assigned if thereis a dependence diagnosis, and should reconsider the number of symptoms required for anabuse or dependence diagnosis.

DSM-IV cannabis abuse and dependence itemIn order to evaluate the individual functioning of the 11 DSM-IV items, we examined both thediscrimination and severity parameters for each item. The symptoms D4 (Problems cuttingdown) and A3 (Legal problems) showed the lowest discrimination values, consistent with thestudy by Martin et al. 23 that examined cannabis and alcohol symptoms in adolescents. Legalproblems also did not load well in two other factor analyses of cannabis items in adults 5, 20,suggesting that this symptom may be problematic in some way. As far as cannabis use disordersgo, Legal problems may not have the same meaning or discriminatory ability that it does foralcohol use disorders. Cannabis is an illicit substance, and even though adolescents showgreater levels of alcohol use than cannabis use, cannabis is currently the top reason foradolescent admissions to treatment 40. Alcohol is also illegal for adolescents (in the U.S.), butperhaps the illicitness of cannabis (for all ages) makes all types of users (casual andproblematic) more likely to encounter legal problems. Overall, the item Legal problems mayneed further study. The symptoms D6 (Activities given up) and D2 (Withdrawal) displayed thehighest discrimination values, suggesting that they are particularly good at identifyingadolescents with significant cannabis problems.

Examination of item severity estimates showed that the level of severity indicated for eachDSM-IV item ranged from 1.87 to 2.87 SD above the population mean (Figure 2), suggestingthat the items are more useful for identifying adolescents with severe cannabis problems. Thedependence items D6 (Activities given up) and D2 (Withdrawal) displayed high severity; alongwith their high discrimination values, these items are likely very useful in identifyingadolescents who have the most severe cannabis problems. Several items – dependence itemsD5 (Time spent obtaining) and D3 (Larger/longer), and abuse items A2 (Use in hazardoussituations) and A4 (Social/interpersonal problems) – displayed similar parameter estimatesand are clustered together in Figure 2, suggesting that they are somewhat redundant. However,these items provide a range of ways to identify adolescents with significant cannabis problems.Overall, the addition of items that identify adolescents with less severe cannabis problemswould be useful.

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Comparing items across samplesWhen we examined whether the item severity estimates differed significantly among the threesamples, we found that they did for two of the cannabis dependence items (Tolerance andLarger amounts/longer period) and for three of the four cannabis abuse items (Figure 4). Thissuggests that some items indicate greater severity of cannabis problems in some populationsmore than others. An IRT analysis of the DSM-IV alcohol items examined this sample andalso found that the same two items, Tolerance and Larger/longer, showed significant DIF(Gelhorn et al., unpublished data). After accounting for mean differences, both of these itemswere endorsed less often in the clinical sample. These two items tend to be more highlyendorsed among adolescents 28, who may naturally experience tolerance or find themselvesconsuming more of the substance than planned by virtue of simply being inexperienced users.In addition, it is interesting that the abuse items generally showed greater populationdifferences, which may help explain why the abuse construct has less statistical support thandoes dependence. One study suggested that the DSM-IV abuse items may be difficult tooperationalize, thus rendering them less reliable 2; however, no other studies have addressedthis issue. Overall, more research is needed to determine the reason for these populationdifferences, and whether they are specific to adolescents. Ideally, the DSM items would notshow these differences.

The findings from this study should be interpreted while considering the following limitations:first, despite the large treatment and community samples, the adjudicated sample was small (n= 172) in terms of the power necessary to perform IRT analyses. Thus, the results for thatsample should be interpreted with caution. Second, while the large community sample wasnearly 50% female, the adjudicated and especially the treatment sample had fewer females.We did not have adequate power to test for sex differences across these samples. Finally, whilethe results for this study are generally consistent with several other studies examining alcoholand other drugs, they are limited to cannabis use in adolescents.

In summary, our study examined the DSM-IV cannabis items in three different samples ofadolescents, representing the largest and most clinically diverse sample to examine thesequestions thus far. Consistent with several other studies examining both alcohol and otherdrugs, we found little evidence to support the abuse-dependence distinction and found thatabuse items can indicate severe substance problems just as dependence items can indicate mildones. The abuse items in particular need further study. These results have implications for therefinement of the current substance use disorder criteria for DSM-V.

Acknowledgements

DA15522, 05131, 12845, 11015, 16314; MH01865; AA07464

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35. Muthen, L.; Muthen, B. Mplus User’s Guide. 3. Los Angeles, CA: Muthen & Muthen; 1998–2004.36. Hulin, C.; Drasgow, F.; Parsons, C. Item Response Theory. Homewood, IL: Dow Jones-Irwin; 1983.37. Kirisci L, Vanyukov MM, Dunn M, Tarter RE. Item response theory modeling of substance use: an

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Associates; 2000.40. SAMHSA. Treatment Episode Data Set (TEDS): 1992–2002, DHHS Pub. # (SMA) 04–3965.

Rockville, MD: 2004.

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Figure 1.Percent endorsement of DSM-IV cannabis abuse and dependence items for each sample

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Figure 2.Item Characteristic Curves for DSM-IV abuse and dependence criteria

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Figure 3.Cannabis item severity estimate comparison across samples, in standard deviations

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Figure 4.Differential Item Functioning (DIF) analysis results for DSM-IV cannabis abuse anddependence items

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Table 1Sample demographics

Sample N Mean Age Gender (%) Ethnicity (%)Combined 5587 15.3 (2.1) M = 58

F = 42Cauc: 78Hisp: 14AA: 3Other: 5

Clinical 615 15.8 (1.2) M = 92F = 8

Cauc: 50Hisp: 37AA: 9Other: 4

Adjudicated 179 16.3 (1.6) M = 77F = 23


Community 4793 15.2 (2.2) M = 53F = 47


Note. Standard deviation in parentheses; Cauc = Caucasian, Hisp = Hispanic, AA = African American, Other = other ethnicity or biracial.


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Item Response Theory Analysis of DSM-IV Cannabis Abuse and Dependence Criteria in Adolescents

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